SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2626–2650 of 3874 papers

TitleStatusHype
Spk2SRImgNet: Super-Resolve Dynamic Scene from Spike Stream via Motion Aligned Collaborative Filtering—0
SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices—0
SPQE: Structure-and-Perception-Based Quality Evaluation for Image Super-Resolution—0
I2UV-HandNet: Image-to-UV Prediction Network for Accurate and High-fidelity 3D Hand Mesh Modeling—0
SREdgeNet: Edge Enhanced Single Image Super Resolution using Dense Edge Detection Network and Feature Merge Network—0
SRFeat: Single Image Super-Resolution with Feature Discrimination—0
SR-GAN for SR-gamma: super resolution of photon calorimeter images at collider experiments—0
SRMAE: Masked Image Modeling for Scale-Invariant Deep Representations—0
SR-NeRV: Improving Embedding Efficiency of Neural Video Representation via Super-Resolution—0
SRNR: Training neural networks for Super-Resolution MRI using Noisy high-resolution Reference data—0
SRN-SZ: Deep Leaning-Based Scientific Error-bounded Lossy Compression with Super-resolution Neural Networks—0
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution—0
SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution—0
SRR-Net: A Super-Resolution-Involved Reconstruction Method for High Resolution MR Imaging—0
SRTGAN: Triplet Loss based Generative Adversarial Network for Real-World Super-Resolution—0
SRTransGAN: Image Super-Resolution using Transformer based Generative Adversarial Network—0
SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution—0
STAR-Pose: Efficient Low-Resolution Video Human Pose Estimation via Spatial-Temporal Adaptive Super-Resolution—0
STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution—0
STARS: Sparse Learning Correlation Filter with Spatio-temporal Regularization and Super-resolution Reconstruction for Thermal Infrared Target Tracking—0
State-of-the-Art Transformer Models for Image Super-Resolution: Techniques, Challenges, and Applications—0
Regional climate risk assessment from climate models using probabilistic machine learning—0
Imitating the Functionality of Image-to-Image Models Using a Single Example—0
Steered Mixture-of-Experts Autoencoder Design for Real-Time Image Modelling and Denoising—0
Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified